Center for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.
Division of Public Health Sciences, Department of Cancer Prevention, Fred Hutchinson Cancer Research Center, Seattle, WA98109, USA.
Br J Nutr. 2021 Sep 14;126(5):773-781. doi: 10.1017/S0007114520004705. Epub 2020 Nov 23.
Higher consumption of 'ultra-processed' (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016-2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.
更高的“超加工”（UP）食品摄入量与不良健康结果有关。本研究旨在根据参与者的社会经济地位（SES）、饮食质量、自我报告的食物支出和能量调整后的饮食成本来描述 UP 食品的能量百分比。在 2016-2017 年于华盛顿州进行的基于人群的西雅图肥胖研究 III （n 755）中，参与者完成了社会人口统计学和食物支出调查以及 FFQ。教育和住宅物业价值是 SES 的衡量标准。FFQ 成分食品的零售价格（n 378）用于估计个体水平的饮食成本。健康饮食指数（HEI-2015）和营养丰富食品指数 9.3（NRF9.3）是饮食质量的衡量标准。超加工食品是按照 NOVA 分类法识别的。多元线性回归用于检验 UP 食品能量与社会人口统计学、两种食物支出估计值和饮食质量衡量标准之间的关联。较高的 UP 食品能量百分比与较高的能量密度、较低的 HEI-2015 和 NRF9.3 评分相关。饮食成本最低的十分位数（每月 216.4 美元）与 67.5%的 UP 食品能量相关；饮食成本最高的十分位数（每月 369.9 美元）与仅 48.7%的 UP 食品能量相关。UP 食品的能量百分比与较低的食物支出和饮食成本呈负相关。在多元分析中，调整协变量后，UP 食品的能量百分比与较低的食物支出、饮食成本和教育相关。UP 食品的能量百分比与较低的食物支出和较低的 SES 相关。减少 UP 食品消费的努力，这是一种越来越常见的政策措施，需要考虑到可负担性、食物支出和饮食成本。
